ExploringtheLimitsofDomain-AdaptiveTrainingfor DetoxifyingLarge-ScaleLanguageModels

Neural Information Processing Systems 

Wethen comprehensively study detoxifying LMswithparameter sizesranging from126Mupto530B(3 largerthanGPT3), a scale that has never been studied before. We find thati) large LMs have similar toxicity levels as smaller ones given the same pre-training corpus, and ii) large LMs require more endeavor to unlearn the toxic content seen at pretraining. Wealso explore parameter-efficient training methods fordetoxification.

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